@inproceedings{765099a5156b42fd8ab471113cb94db5,
title = "Asynchronous and Decentralized Multiagent Trajectory Planning in Dense Environments",
abstract = "This paper proposes an online decentralized and asynchronous multiagent trajectory planning algorithm in dense environments. In our algorithm, the optimization problem is transformed into a quadratic programming (QP) problem to reduce the computational complexity by constructing the optimal linear flight corridors (OLFC). A cooperation-based deconfliction framework is designed to ensure the safety and feasibility under the decentralized and asynchronous architecture. We conduct a large number of simulations to verify the reliability and efficiency of our algorithm in dense environments with higher success rate, less computational time and total navigation time, which is more aggressive and cooperative.",
keywords = "Decentralized system, Linear flight corridor, Multiagent, Trajectory planning",
author = "Zhengxiang Guo and Jinwen Hu and Chunhui Zhao and Quan Pan",
note = "Publisher Copyright: {\textcopyright} 2023, Beijing HIWING Sci. and Tech. Info Inst.; International Conference on Autonomous Unmanned Systems, ICAUS 2022 ; Conference date: 23-09-2022 Through 25-09-2022",
year = "2023",
doi = "10.1007/978-981-99-0479-2_15",
language = "英语",
isbn = "9789819904785",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "153--162",
editor = "Wenxing Fu and Mancang Gu and Yifeng Niu",
booktitle = "Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022",
}